Perceived Usefulness, Competency, and Associated Factors in Using District Health Information System Data Among District Health Managers in ...
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JMIR FORMATIVE RESEARCH Simba et al
Original Paper
Perceived Usefulness, Competency, and Associated Factors in
Using District Health Information System Data Among District
Health Managers in Tanzania: Cross-sectional Study
Daudi Simba1, PhD; Felix Sukums2, PhD; Claud Kumalija3, MSc; Sarah Eden Asiimwe4, MD; Sai Kumar Pothepragada4,
MD; Patrick Warui Githendu4, BSc
1
Department of Community Health, Muhimbili University of Health and Allied Sciences, Dar es Salaam, United Republic of Tanzania
2
Directorate of Information and Communication Technology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, United Republic of
Tanzania
3
Health Management Information System Unit, Ministry of Health, Community Development, Gender, Elderly and Children, Dodoma, United Republic
of Tanzania
4
The Global Fund to Fight HIV, Tuberculosis and Malaria, Geneva, Switzerland
Corresponding Author:
Felix Sukums, PhD
Directorate of Information and Communication Technology
Muhimbili University of Health and Allied Sciences
Box 65001
Dar es Salaam, 255
United Republic of Tanzania
Phone: 255 713238473
Email: Sukums@gmail.com
Abstract
Background: Tanzania introduced District Health Information Software (version 2; DHIS2) in 2013 to support existing health
management information systems and to improve data quality and use. However, to achieve these objectives, it is imperative to
build human resource capabilities to address the challenges of new technologies, especially in resource-constrained countries.
Objective: This study aimed to determine the perceived usefulness, competency, and associated factors in using DHIS2 data
among district health managers (DHMs) in Tanzania.
Methods: This descriptive cross-sectional study used a quantitative approach, which involved using a self-administered web-based
questionnaire. This study was conducted between April and September 2019. We included all core and co-opted members of the
council or district health management teams (DHMTs) from all 186 districts in the country. Frequency and bivariate analyses
were conducted, and the differences among categories were measured by using a chi-square test. P values ofJMIR FORMATIVE RESEARCH Simba et al
(JMIR Form Res 2022;6(5):e29469) doi: 10.2196/29469
KEYWORDS
DHIS2; Tanzania; health information system; health management information system; perception; competency; usefulness
additional demand by partners for timely measurement of results
Introduction [11].
Background Since then, several reviews have been conducted to identify
Health information systems (HISs) are 1 of the 6 building blocks bottlenecks and address them to improve HISs. The review
of the health system [1] and are crucial in addressing health conducted before the introduction of the DHIS2 showed that
challenges and improving health service delivery in reporting systems were weak, both in terms of completeness
resource-limited countries [2]. However, many resource-limited and timeliness [13].
countries face challenges in improving their HISs using Consequently, the Ministry of Health, in collaboration with
information and communication technology (ICT) [3]. The implementing and development partners who support various
advent of a free and open-source web-based District Health health service activities, including the DHIS2 implementation,
Information Software (version 2; DHIS2) signaled a new era created the Monitoring and Evaluation Strengthening Initiative
by providing a solution for addressing one of the major in 2010, whose vision was to have a comprehensive platform
challenges in HISs [4], that is, the availability of quality and for health information, evidence-based decision-making, and
timely data for planning and evaluating health sector accountability for results [14]. The key strategic objective was
performance [5]. the introduction of the DHIS2. Tanzania adopted the DHIS2 as
DHIS2 is a tool for the collection, validation, analysis, and a national health management information system (HMIS)
presentation of aggregate data, tailored to facilitate integrated platform in 2010, and by December 2013, all districts in the
health information management activities and inform country were using the system. The system was customized to
decision-making [3,6]. The software is based at the district level capture and process all routine aggregate data collected monthly
and derives primary data from paper-based monthly reports of from all health facilities, including public and nonpublic
health facilities. As a web-based system in a centralized server, facilities [15,16].
DHIS2 presents a more stable solution compared with the ICT has an impact when people have the necessary competencies
previous HIS solutions [7]. With DHIS2, anyone with a to develop and use it; otherwise, the system becomes a waste
computing device connected to the internet, a system username, of resources [17]. Although ICT has been introduced to help
and a password can view data anywhere as soon as it is entered manage resources and increase efficiency, many resource-limited
[8]. countries face a severe shortage of appropriate human resources,
The DHIS2 is a simplified generic tool based on an open both in terms of quantity (numbers) and quality (skills)
metadata model and a flexible user interface that does not [6,15,18]. The implementation of the DHIS2 in Tanzania, as in
require a preconfigured database application [9]. Users can other resource-constrained countries that have adopted the
customize the software package according to their information system, is likely to suffer from poor and unevenly developed
needs without the need to have advanced programming skills infrastructure, inadequate competencies among the workforce
or learn complex programming language [8-10]. The ultimate to support the system, and the use of information for
aim of DHIS2 is to establish a centralized database that connects decision-making [11]. To maximize return on investment,
service delivery with other health systems [11]. implementers of the DHIS2 need to address the major
challenges, including skill deficiencies in the workforce [18].
DHIS2 has several modules and features that make it superior Other factors affecting the successful implementation of an
to the previous HIS software used in sub-Saharan African electronic HISs include positive attitudes toward the HISs,
countries [9]. Its features include customizable data entry forms confidence in using computers and the HISs, and fast and
with indicators; data visualizers, such as graphs, web-based reliable internet connectivity. These factors need to be regularly
pivot tables, and dashboards; an integrated geographic monitored, and challenges affecting the effective use of an
information system module; import and export metadata; electronic HISs must be addressed to promote a data culture for
customizable data quality checks; user access control; and evidence-informed decision-making [19]. However, there is
messaging and mobile solutions. Other modules include a patient limited information on district health managers’ (DHMs)
tracker and mobile app and are interoperable with other systems perceptions and competencies in using the DHIS2 and its data
[12]. for informed decision-making in Tanzania.
The DHIS2 in Tanzania
Over the past decade, the Tanzanian health sector has seen an
Methods
increasing focus on strengthening its national HIS. This followed Aim of This Study
a wind of change that swept across other African countries south
of the Sahara because of accelerated disease control initiatives, This study aimed to determine the perceived usefulness of
specifically HIV, tuberculosis, and malaria, which created DHIS2 and its competency in using generated data among
DHMs, who are the primary target beneficiaries of the system.
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Study Design district, both core and co-opted members of the DHMTs
This is a descriptive cross-sectional analytic study that used a (approximately 15) were interviewed.
quantitative approach to gather information on the perceived At the beginning of this study, the researchers (DS, FS, and
usefulness of the DHIS2, the competencies of DHMs, and CK) collected the names, email addresses, and phone numbers
factors associated with the use of DHIS2 data to improve health of all DHMs from among the regional HMIS focal persons.
services. Factors associated with DHIS2 use, according to the Data managers linked DHMs to the web-based questionnaire
Performance of Routine Information System Management through their email addresses, and phone numbers were used
framework, were categorized as technical, organizational, and to follow up on nonresponders and to communicate data
behavioral issues [20]. Respondents were not only given an discrepancies. The email addresses were collected on a separate
opportunity to select from predefined factors but also given the sheet and used only by the data managers for follow-up during
freedom to specify other issues affecting the use of the DHIS2 data collection. No identifiable personal information was
and its data. included in this questionnaire.
Study Setting Data Collection Approaches
Tanzania is an East African country made up of the mainland This study was conducted between April and September 2019.
and islands of Zanzibar and is the largest country in the East We developed a questionnaire containing different aspects of
African Community. It spreads over 947,300 km2 of land, is the DHIS2, data management and use. The questionnaire had
multiethnic, and has wide cultural diversity. At the time of this several sections, including sociodemographic information,
study, Tanzania was a low-income country, with a gross respondents’ self-rated skill levels on basic computer
domestic product per capita of 957 and a growth rate of 6.8%. applications and the DHIS2, and skills on data use for various
The Tanzania Mainland alone is estimated to have a population purposes. The questionnaire also had a section that assessed
of 55 million, distributed in 26 regions and 186 districts. The perceived usefulness, ease of use, and user satisfaction with the
country has >8000 health facilities, offering a wide range of DHIS2 [22]. The perception statements were rated on a 5-point
health care services [21]. Likert scale, ranging from 1 (strongly disagree) to 5 (strongly
agree), covering managers’ experience and perception of the
The health system in Tanzania is well organized in a hierarchical
application of the DHIS2 in their work, its perceived benefits,
structure from the community to the national level. It is a
and their willingness and ability to use the DHIS2 and data from
decentralized system, whereby local government authorities are
the system for various decision-making processes. The
responsible for the planning and management of primary health
availability of ICT support from the councils as well as
service delivery. At the primary level, there are district hospitals,
challenges hindering the implementation and use of DHIS2
health centers, and dispensaries. The DHMs are responsible for
were also included in the questionnaire.
district health planning, resource allocation, implementation of
health interventions, and supervision of health service provision The questionnaires, translated into Kiswahili, were formatted
in primary health care settings. Thus, it is paramount to assess using Google Forms to ease the filling and submission by
the perception and competencies of DHMs regarding the use respondents via an internet-enabled device with an internet
of the DHIS2 and its data in accomplishing their core functions. browser. Furthermore, the questionnaires had mandatory quality
checks to ensure that all relevant fields had been filled in before
We defined the use of DHIS2 to include the entire process from
submission of the data into a database.
data entry, navigation through the DHIS2 application, data
validation, data analysis, and production of visualizations. We A total of 26 field staff members, 1 from each of the 26 regions,
defined data use as the reported use of DHIS2 data for the were recruited to facilitate data collection. The field staff
planning and implementation of activities, for example, for comprised regional HMIS focal persons, who are government
planning, staff deployment, allocation of funds, procurement officials assigned with the responsibility to oversee HMIS
of medicine and supplies, and production of league tables. activities in their respective regions. The regional HMIS focal
persons received a half-day orientation on the study objectives
Study Population and data collection procedures during the 2019 annual regional
All core and co-opted members of the district health HMIS focal persons meeting. They were also tasked to provide
management teams (DHMTs) were included. Core members the names and addresses of members of all DHMTs in their
were recruited based on their professional cadre. These included respective regions. Data managers later used these to send
the district medical officer, who is a medical doctor, and the questionnaires to the respondents, who had to provide consent,
district health officer, who is an environmental health scientist fill in the questionnaire, and submit their responses on the web
by profession. Co-opted members are program coordinators to a server located at the Muhimbili University of Health and
who are invited to the DHMT from time to time when issues Allied Sciences (MUHAS) offices. Field staff made follow-up
pertaining to their programs are discussed. These include the visits to the respective districts to ensure the completion of the
reproductive and child health, HIV, tuberculosis, and malaria questionnaires.
programs.
Data managers and researchers (DS and FS) scrutinized the
Sampling Strategy and Sample Size submitted data daily for duplicate submissions, incomplete
Data were collected to represent the entire country; hence, 186 questionnaires, and discrepancies. When duplicate forms were
districts in all 26 regions in the country were included. In each dropped, incomplete questionnaires and discrepancies were
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communicated to the respondents before making the necessary Ethical Clearance
corrections in the database. In addition, the types of errors Ethical clearance was obtained from the institutional review
observed were communicated to the field staff, who used this board of MUHAS, Tanzania (reference number
information to guide respondents on proper filling in of the DA.282/298/01.C). Permission to implement this research was
questionnaires during on-site follow-up visits. This helped to obtained from the Ministry of Health, Community Development,
avoid the recurrence of similar mistakes. Gender, Elderly, and Children and the President Office Regional
The questionnaire was pretested with staff at Muhimbili National Administration and Local Government. Written informed
Hospital and MUHAS in Dar es Salaam to ascertain the ease consent was obtained from all participants. No identifiable
of filling in the questionnaires and to ensure that the questions personal information regarding the respondents was collected.
were clearly understood. The findings from the pretest were The research data were kept secure and confidential by 2
used to improve on the tools before distributing them to the researchers (DS and FS) and 2 data managers.
respondents.
Results
Data Analysis
Data analysis was performed using SPSS (version 20; IBM General Characteristics
Corporation) software. Frequency tables were prepared to assist Responses from DHMs were received from all 186 district
in data cleaning. Data were presented using tables and charts councils in the 26 regions in Tanzania Mainland. A total of 2667
with comparisons of different categories. Bivariate analyses (77.96%) of the expected 3421 DHMs responded, of which
were conducted to determine the relationships among the 2598 (97.41%) consented and completed the questionnaires.
selected variables. Differences among categories were measured More than half (1466/2598, 56.43%) of the respondents were
using the chi-square test. PJMIR FORMATIVE RESEARCH Simba et al
Table 1. Sociodemographics of participants (N=2598).
Characteristics Values, n (%)
Sex
Female 1132 (43.57)
Male 1466 (56.43)
Age (years)
20-34 852 (32.79)
35-49 1291 (49.69)
≥50 455 (17.51)
Profession
Medical 2038 (78.44)
Nonmedical 560 (21.56)
Work experience (years)
1-5 740 (28.48)
6-10 714 (27.48)
≥11 1144 (44.03)
Title
Core district health management team members 1097 (42.22)
Program coordinators 834 (32.1)
Others 667 (25.67)
Education
Degree holders 1312 (50.5)
Nondegree holders 1286 (49.5)
English proficiency
Very fluent 572 (22.02)
Fluent 1221 (47)
Average 805 (31.98)
Opinions of Respondents on the Use of the DHIS2
Perceived Usefulness of the DHIS2
As indicated in Table 2, DHMs were asked about their opinions
DHMs were asked for their opinions on the usefulness of
on several issues pertaining to the usefulness of DHIS2 and the
DHIS2. Most responses indicated that DHIS2 contributed to
ease of use of the system. Overall, most DHMs expressed
improved data quality (2239/2598, 86.18%) and reduced
satisfaction with the system, explaining that the system was
workload (2123/2598, 81.72%). Furthermore, 86.64%
good for their work (2288/2598, 88.07%) and enabled them to
(2251/2598) of the respondents indicated that DHIS2 use has
be more effective (2187/2598, 84.18%). When asked if the
improved data availability (Multimedia Appendix 1).
system was confusing and difficult to learn and understand,
most DHMs disagreed, as 66.05% (1716/2598) said it was not
confusing and 75.17% (1953/2598) said it was not difficult to
learn and understand.
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Table 2. Opinions of respondents on the use of District Health Information Software (version 2; DHIS2; N=2598).
Opinion statements based on perception Not sure, n (%) Disagree, n (%) Agree, n (%)
The DHIS2 enhances data use 233 (8.97) 126 (4.85) 2239 (86.18)
The DHIS2 enables effective completion of work 283 (10.89) 128 (4.93) 2187 (84.18)
The DHIS2 is good for my work 225 (8.66) 85 (3.27) 2288 (88.07)
The DHIS2 is confusing 527 (20.28) 1716 (66.05) 355 (13.66)
The DHIS2 is difficult to learn and understand 410 (15.78) 1953 (75.17) 226 (8.7)
Generally, I am satisfied with the DHIS2 321 (12.36) 203 (7.81) 2074 (79.83)
(2390/2598, 91.99%) members of the DHMT reported having
Levels of Basic Computer Skills either average or advanced skills in DHIS2 use.
For the DHMs to be able to use the DHIS2 as a tool, they ought
to have skills in basic computer operations and applications and A bivariate analysis was performed on some of the factors likely
use of the DHIS2 software. Respondents were assessed using to be associated with respondents’ skills in DHIS2 use. Table
self-rated questions to establish their skill levels regarding 3 provides the association between respondents’ ability to use
various ICT issues. As indicated in Multimedia Appendix 1, the DHIS2 and their sex, profession, title, and level of English
slightly more than half (1377/2598, 53%) of the DHMs reported proficiency. Male respondents, medical professionals, core
having advanced skills in basic computer operations, file members of the DHMT, and those with very high levels of
management (1439/2598, 55.39%), Microsoft Word (1404/2598, proficiency in English were more likely to have higher skills in
54.04%), and internet use (1298/2598, 49.96%). Almost all the use of the DHIS2 compared with their counterparts. The
differences were statistically significant.
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Table 3. Bivariate analysis of factors associated with respondents’ self-rated skill levels in District Health Information Software (version 2) use
(N=2598).
Characteristics Level of respondents’ skills in using the District Health Information Software (version 2), P value
n (%)
None Average Advanced Total
Sex .005
Male 95 (7) 883 (65.12) 378 (27.88) 1356 (100)
Female 113 (9.98) 733 (64.75) 286 (25.27) 1132 (100)
Age (years) .23
20-34 75 (8.8) 564 (66.2) 213 (25) 852 (100)
35-49 90 (6.97) 855 (66.23) 346 (26.72) 1291 (100)
≥50 43 (7.89) 307 (56.33) 195 (35.78) 545 (100)
Profession .01
Nonmedical 60 (10.71) 374 (66.78) 126 (22.5) 560 (100)
Medical 148 (7.26) 1352 (66.34) 538 (26.4) 2038 (100)
Experience (years) .56
1-5 65 (8.78) 501 (67.7) 174 (23.51) 740 (100)
6-10 52 (7.28) 473 (66.25) 189 (26.47) 714 (100)
≥11 91 (7.95) 752 (65.73) 301 (26.31) 1144 (100)
Title .004
Core district health management team 78 (7.11) 701 (63.9) 318 (28.99) 1097 (100)
members
Program coordinators 70 (8.39) 558 (66.91) 206 (24.7) 834 (100)
Others 60 (9) 457 (68.52) 140 (20.99) 667 (100)
Education level .25
Nondegree 102 (7.93) 837 (65.09) 347 (26.98) 1286 (100)
Degree 106 (8.14) 880 (67.54) 317 (24.33) 1303 (100)
English proficiency .001
Very high (80%-100%) 52 (6.52) 446 (55.96) 299 (37.52) 797 (100)
High (60%-69%) 87 (7.07) 879 (71.46) 264 (21.46) 1230 (100)
Average (JMIR FORMATIVE RESEARCH Simba et al
Table 4. Bivariate analysis of factors associated with training in District Health Information Software (version 2) data analysis (N=2598).
Characteristics Not trained, n (%) Trained, n (%) Total, n (%) P value
Sex .004
Male 732 (49.93) 734 (50.07) 1466 (100)
Female 629 (55.57) 503 (44.43) 1132 (100)
Age (years) .001
20-34 499 (58.57) 353 (41.43) 852 (100)
35-49 650 (50.35) 641 (49.65) 1291 (100)
≥50 212 (46.59) 243 (53.41) 455 (100)
Profession .001
Nonmedical 342 (61.07) 218 (38.93) 560 (100)
Medical 1019 (50) 1019 (50) 2038 (100)
Experience (years) .001
1-5 444 (60) 296 (40) 740 (100)
6-10 381 (53.36) 333 (46.64) 714 (100)
≥11 536 (46.85) 608 (53.15) 1144 (100)
Title .001
Core district health management team members 572 (52.14) 525 (47.86) 1097 (100)
Program coordinators 400 (47.96) 434 (52.04) 834 (100)
Others 389 (58.32) 278 (41.68) 667 (100)
Education level .001
Nondegree 618 (48.06) 668 (51.94) 1286 (100)
Degree 743 (56.63) 569 (43.37) 1312 (100)
English proficiency .003
Very high (80%-100%) 377 (47.3) 420 (52.7) 797 (100)
High (60%-69%) 673 (54.72) 557 (45.28) 1230 (100)
Average (JMIR FORMATIVE RESEARCH Simba et al
Table 5. Factors associated with the ability of district health managers to use District Health Information Software (version 2) data (N=2598).
Characteristics Ability to use District Health Information Software (version 2) data, n (%)a P value
None Basic Average Advanced Total
Sex .001
Male 29 (1.98) 635 (43.32) 337 (22.99) 465 (31.72) 1466 (100)
Female 30 (2.65) 583 (51.5) 238 (21.02) 281 (24.82) 1132 (100)
Age (years) .11
20-34 23 (2.7) 406 (47.65) 175 (20.54) 248 (29.12) 852 (100)
35-49 30 (2.32) 577 (44.69) 301 (23.32) 383 (29.67) 1291 (100)
≥50 6 (1.32) 235 (51.65) 99 (21.76) 115 (25.27) 455 (100)
Profession .01
Nonmedical 10 (1.79) 296 (52.86) 117 (20.89) 137 (24.46) 560 (100)
Medical 49 (2.4) 922 (45.24) 458 (22.47) 609 (29.88) 2038 (100)
Experience (years) .049
1-5 18 (2.43) 368 (49.73) 153 (20.68) 201 (27.16) 740 (100)
6-10 22 (3.08) 302 (42.3) 165 (23.11) 225 (31.51) 714 (100)
≥11 19 (1.66) 548 (47.9) 257 (22.47) 320 (27.97) 1144 (100)
Title .001
Core district health management team 22 (2.01) 472 (43.03) 238 (21.7) 365 (33.27) 1097 (100)
members
Program coordinators 19 (2.28) 394 (47.24) 185 (22.18) 236 (28.3) 834 (100)
Others 18 (2.7) 352 (52.77) 152 (22.79) 145 (21.74) 667 (100)
Education level .46
Nondegree 32 (2.49) 592 (46.03) 299 (23.25) 363 (28.23) 1286 (100)
Degree 27 (2.06) 626 (47.71) 276 (21.04) 383 (29.19) 1312 (100)
English proficiency .001
Very high (80%-100%) 18 (2.26) 283 (35.51) 165 (20.7) 331 (41.53) 797 (100)
High (60%-69%) 26 (2.11) 598 (48.62) 292 (23.74) 314 (25.53) 1230 (100)
Average (JMIR FORMATIVE RESEARCH Simba et al
Table 6. Perceived challenges hindering the implementation and use of the District Health Information Software (version 2; N=2598).
Challenges affecting the use of District Health Information Software (version 2) Participants, n (%)
There is a lot of paperwork 1890 (72.75)
Inadequate technical support 1566 (60.28)
Inadequate information and communication technology officers 1734 (66.74)
Unreliable internet connectivity 1670 (64.28)
Slow internet speed 1552 (59.74)
Data quality compromised during data processing 1307 (50.31)
Lack of guidelines for filling out the main data sources and reporting forms 1190 (45.8)
Data collection and reporting forms are not standardized; some groups have their own formats 1028 (39.57)
Lack of feedback 986 (37.95)
Electrical power interruption or unreliable electricity 895 (34.45)
Parallel data systems collecting the same indicators 814 (31.33)
Data collection and reporting forms are not standardized; some groups have their own formats 733 (28.21)
Data overload: data management operational processes are not documented 675 (25.98)
Personnel are not trained in the use of data sources and reporting forms 596 (22.94)
the data from anywhere [8,11]. In Tanzania, the DHIS2 has
Discussion integrated >15 intervention programs and several digital HISs,
Principal Findings including human resources for HISs and health facility registries
[16]. The creation of a central data warehouse on a central
In this study, most (2074/2598, 79.83%) DHMs reported web-based server integrated with other digital HISs makes the
satisfaction with the DHIS2, stating that it improved their quality DHIS2 a robust source of information and ensures better access
of work and made their daily work effective. This study shows to data and information by users [11,24,29-31].
that DHMs have appreciable competencies in using the DHIS2
and its data. Some challenges have been identified, and The DHMs’ satisfaction with data quality emanates from the
recommendations have been made for the improvement of DHIS2 data validation tools that simplify consistency checks
access to and use of DHIS2 data. Similar findings have been compared with when the exercise was performed on a
reported in other countries that implemented the DHIS2, where paper-based system [9]. As the DHIS2 brings together data from
health workers were reported to be satisfied with the ease of various programs, data triangulation can be performed easily
data processing [11,23,24]. In addition, the perception of health and discrepancies, identified [15]. Moreover, the ease in
workers regarding the use of health information technology, accessing DHIS2 data has exposed more people to it, which has
such as DHIS2, is influenced by user-friendliness and the facilitated feedback and self-assessment, making it easier for
perceived benefits of the system [25]. Although in these studies DHMs to identify errors for prompt correction [4,24].
the reported satisfaction was limited to the use of the application DHMs’ satisfaction with reduced workload burden can be
(in data processing), our study went further to reveal satisfaction explained by the ability of the DHIS2 modules to produce
with the outcomes of using the application. Furthermore, in this standardized tables and allow tailor-made reports to be prepared
study, >80% of the DHMs in Tanzania indicated a high level by users using pivot tables [9].
of commitment to using the DHIS2, as they perceived the system
to have improved data quality, reduced workload, and improved The high level of satisfaction with the software reflects the
data use and decision-making (Table 2). This is above the readiness of DHMs to develop further, which can be taken as
commitment levels reported in other studies in Ethiopia, Ghana, an opportunity for the DHIS2 implementers or Ministry of
Nigeria, and Iran [26]. Health to strengthen the strategy for increasing data demand
and use, which is currently a major challenge [32].
The high rate of satisfaction reported in our study was attributed
to the improved availability and quality of routine data and the Almost all (2390/2598, 91.99%) DHMs reported having at least
reduction in workload burden for DHMs. Before the introduction basic-level skills on the DHIS2, whereas half of them (664/2598,
of the DHIS2, availability and quality of routine data were 25.56%) reported having advanced skills. To our knowledge,
unsatisfactory [13,27]. Reporting systems were weak, and user this is the first study to quantify and report the competencies of
satisfaction with usability was low. The situation changed after health managers in using the DHIS2 and data generated from
the introduction of the DHIS2, where completeness and it.
timeliness of reporting were maintained at a very high rate [28]. One of the major factors that might have contributed to such a
Improved data availability can be attributed to the web-based level of competency is the introduction of the DHIS2 on an
feature of DHIS2 with a centralized server that simplifies data existing paper-based HISs, which was relatively well developed
entry and access and enables anyone with access rights to view with functioning structures and materials for data collection,
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reporting, and analysis [33]. In addition, the training of DHMs organizational culture of data demand and use for
was based on hands-on practice for data analysis using actual decision-making [36].
data, the provision of technical support and supportive
DHMs play a central role in the planning and implementation
supervision, and the distribution of computers and accessories
of primary health care services in a decentralized country such
to all districts immediately after the training. Furthermore, the
as Tanzania [34]. The reported competency in using DHIS2
high level of competencies is likely to be because of the
data found in this study is likely to have a multiplier effect at
decentralization of governance in the districts, which has
the health facility level, where decisions made by DHMs have
provided them authority for decision-making in the planning
a profound effect, and at the national level, where DHMs are
and implementation of interventions [34]. The extensive use of
held accountable for resources invested in district health
data from the DHIS2 during the preparation of Comprehensive
services.
Council Health Plans through the Planning and Reporting system
(PlanRep) [35] may also explain why more DHMs reported a Methodological Considerations of This Study
higher level of competency in the use of DHIS2 data for The findings of this study are self-reported; hence, they are
planning compared with other purposes. likely to be overestimated for respondents who want to
Program coordinators received more training in data analysis exaggerate their capacity in the hope of being applauded or may
compared with other members of the DHMT. This can be underestimate their capacity in the hope of receiving more
explained by the fact that training for continuing education in support. Studies have indicated that respondents prefer to attend
many districts is supported by implementing and development training or meetings because of the allowances paid—the per
partners through their respective intervention programs. In such diem syndrome [37-39]. In this case, some respondents may
training, program managers are given priority, whereas other prefer to underestimate their level of knowledge so that they
members are often left out because of limited funding. can get opportunities to attend training for the sake of receiving
allowances. Therefore, it is difficult to predict the direction of
In this study, only half (1380/2598, 53.12%) of the DHMs bias likely to result from the reported data.
reported having access rights to the DHIS2 application. Similar
findings were reported in a study conducted in Kenya, where The web-based administration of questionnaires enables access
approximately half of the health workers in the studied health to large and different populations, and it is an inexpensive,
facilities reported having no access rights, and as a result, they quick, and convenient approach to collecting data [40-42].
did not use the DHIS2 data [4]. Challenges in having access However, this approach has the disadvantage of having relatively
rights undermine the strength of the DHIS2 in ensuring that lower response rates compared with face-to-face administration
DHMs have prompt access to information for decision-making [40]. Nevertheless, in this study, the response rate was higher
[8,11]. Nevertheless, we report a higher proportion of DHMs (75.9%) than the mean response rate for web-based data
using the DHIS2 than those reporting to have DHIS2 user collection approaches reported by Blumenberg and Barros [40].
accounts. In addition to sharing accounts among DHIS2 users, Furthermore, the scope of this study was limited to determining
this may also indicate peer or self-learning, a phenomenon that DHMs’ perceived competency in using DHIS2 and the generated
is uncommon in the country’s health sector [18]. data. The quantitative nature of this study prevented us from
Finally, we report challenges in the provision of a supporting answering some pertinent practical questions. Questions such
environment that is likely to have undermined the competency as “What is behind the reported success in Tanzania?” will
of DHMs in using the DHIS2 application and the generated require qualitative studies to answer them.
data. These include inadequate support for ICT, including
Strengths of Our Study
computers and internet connections and insufficient funds at
the district level. Interestingly, the level of achievement attained This is the first study to report the competencies of DHMs in
with only half of the expected resources is appreciably high. using the DHIS2 application and the generated data. This study
This indicates that there is a high potential for improvement if gathered primary data from the DHMs in 186 districts in the
more resources are available to DHMs. country. In this study, we quantified the level of satisfaction
with the DHIS2 application among DHMs, its usefulness, and
Implications of the Study Findings their competencies in using the application and generated data.
Training in DHIS2 use has been cited in the literature as one of
Conclusions
the challenges affecting the establishment and effective use of
the system [10]. The fact that almost all (2390/2598, 91.99%) DHIS2 modules have enhanced availability and quality of data
DHMs reported having at least basic computer and DHIS2 and reduced workload burden compared with the situation that
application skills provides a favorable environment for existed before its commencement. This has led to satisfaction
upgrading to the advanced level. As the proportion of DHMs with the application by most (2187/2598, 84.18%) DHMs
who reported having advanced skills in the use of DHIS2 data because of improved quality of work and their effectiveness.
was dismal, it is still adequate to form a critical mass that can Although almost all (2564/2598, 98.69%) DHMs reported to
be used to prepare data use champions. These can then be have at least basic skills on DHIS2, approximately one-fourth
deployed to provide on-the-job peer education; supportive of them (746/2598, 28.71%) reported having high-level skills.
supervision; and mentoring to all members of the DHMT, The Ministry of Health needs to seize this opportunity to train
irrespective of their cadre; with the aim of strengthening the the few DHMs with high-level skills to enable them to support
the majority who have basic-level skills in data use for
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decision-making. Further research is needed to determine the extent to which the competencies are translated into data use
factors that influence the reported DHMs’ competency and the for decision-making to improve health care services.
Acknowledgments
The authors are grateful to the management of the Ministry of Health, Community Development, Gender, Elderly and Children
and the President Office Regional Administration and Local Government for allowing them to carry out this research at their
sites. The authors also thank the members of the Regional Health Management Teams and district health management teams for
providing valuable support during this study. This study was funded by the Global Fund to fight HIV, tuberculosis, and malaria.
The funder did not have any role in the study design, data collection and analysis, decision to publish, or manuscript preparation.
The manuscript writing was not supported financially.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Supplementary Tables 1-6.
[DOCX File , 25 KB-Multimedia Appendix 1]
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Abbreviations
DHIS2: District Health Information Software (version 2)
DHM: district health manager
DHMT: district health management team
HIS: health information system
HMIS: health management information system
ICT: information and communication technology
MUHAS: Muhimbili University of Health and Allied Sciences
Edited by A Mavragani; submitted 12.04.21; peer-reviewed by A Garcia, D Palazuelos, MDG Pimentel, R Dong; comments to author
28.06.21; revised version received 14.07.21; accepted 27.12.21; published 23.05.22
Please cite as:
Simba D, Sukums F, Kumalija C, Asiimwe SE, Pothepragada SK, Githendu PW
Perceived Usefulness, Competency, and Associated Factors in Using District Health Information System Data Among District Health
Managers in Tanzania: Cross-sectional Study
JMIR Form Res 2022;6(5):e29469
URL: https://formative.jmir.org/2022/5/e29469
doi: 10.2196/29469
PMID:
©Daudi Simba, Felix Sukums, Claud Kumalija, Sarah Eden Asiimwe, Sai Kumar Pothepragada, Patrick Warui Githendu. Originally
published in JMIR Formative Research (https://formative.jmir.org), 23.05.2022. This is an open-access article distributed under
the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is
properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well
as this copyright and license information must be included.
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